Halodoc Adoption Model: Integration of UTAUT2, Perceived Risk, and Trust with PLS-SEM
DOI:
https://doi.org/10.46984/sebatik.v29i2.2704Keywords:
Perceived risk, PLS-SEM, telemedicine, trust, UTAUT2Abstract
The development of digital health technology, also known as healthtech, has transformed the opportunities and ways people access healthcare, particularly through telemedicine. In Indonesia, Halodoc has become one of the most widely used telemedicine platforms, offering easy access and affordable online healthcare services. Despite its various conveniences, user adoption remains inconsistent due to persistent issues and public perceptions regarding perceived risk and lack of trust in online consultation methods. This study aims to develop a model for Halodoc adoption by developing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) with perceived risk and trust in medical personnel. Using a quantitative approach, data responses were collected from online Halodoc users through purposive sampling and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) techniques with the help of SmartPLS. The results show that only facilitating conditions, habit, and price value have a significant influence on behavioral intention to adopt Halodoc. Extensive factors suspected of influencing Halodoc adoption, namely perceived risk and trust in medical personnel, did not have a significant influence, especially in the Indonesian context. The results of this study add to the role and benefits of UTAUT2 in the healthcare context, especially in Indonesia, with managerial implications for enhancing the role of facilitating conditions, habits, and price value in order to increase the adoption of Halodoc and other digital healthcare in Indonesia.
References
Anderson, L. A., & Dedrick, R. F. (2017). Development of the Trust in Physician Scale: A Measure to Assess Interpersonal Trust in Patient-Physician Relationships. Psychological Reports, 67(3_suppl), 1091–1100. https://doi.org/10.2466/pr0.2017.67.3f.1091
Chrisdianti, G. O., Handayani, P. W., Azzahro, F., & Yudhoatmojo, S. B. (2023). Users’ Intention to Use Mobile Health Applications for Personal Health Tracking. In Journal of Information System) (Vol. 19, Issue 1).
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
Featherman, M. S., & Pavlou, P. A. (2020). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3
Grewal, D., Gotlieb, J., & Marmorstein, H. (2021). The Moderating Effects of Message Framing and Source Credibility on the Price-Perceived Risk Relationship. Journal of Consumer Research, 21(1), 145. https://doi.org/10.1086/209388
Hair, J. F., Hult, G. T., Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)—Joseph F. Hair, Jr., G. Tomas M. Hult, Christian Ringle, Marko Sarstedt. In Sage.
Hair, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2016). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128
Hawa, T., Putri Paramita, E., Miharja, D. L., Trisula, Y., & Yohanes, S. (2023). PERSEPSI PENGGUNA APLIKASI HALODOC TERHADAP PENINGKATAN LITERASI KESEHATAN DI KOTA MATARAM. Jurnal Ilmiah Mahasiswa Komunikasi Universitas Mataram, 4(2), 26–32.
Hayat, N., Al Mamun, A., Gao, J., Yang, Q., & Hussain, W. M. H. W. (2024). Envisaging the intention and adoption of electronic health applications among middle-aged and older adults: Evidence from an emerging economy. Digital Health, 10. https://doi.org/10.1177/20552076241237499
Jiao, W., Chang, A., Ho, M., Lu, Q., Liu, M. T., & Schulz, P. J. (2023). Predicting and Empowering Health for Generation Z by Comparing Health Information Seeking and Digital Health Literacy: Cross-Sectional Questionnaire Study. Journal of Medical Internet Research, 25, e47595. https://doi.org/10.2196/47595
Kuen, L., Schürmann, F., Westmattelmann, D., Hartwig, S., Tzafrir, S., & Schewe, G. (2023). Trust transfer effects and associated risks in telemedicine adoption. Electronic Markets, 33(1). https://doi.org/10.1007/s12525-023-00657-0
Kurnia, F. (2021). Pengembangan Niat Adopsi Mobile Wallet: Integrasi Model UTAUT2 dengan Social Connectedness dan Culture. Jurnal Rekayasa Sistem Industri, 10(2), 145–160. https://doi.org/10.26593/jrsi.v10i2.4374.145-160
Lu, H. H., Lin, W. S., Raphael, C., & Wen, M. J. (2023). A study investigating user adoptive behavior and the continuance intention to use mobile health applications during the COVID-19 pandemic era: Evidence from the telemedicine applications utilized in Indonesia. Asia Pacific Management Review, 28(1), 52–59. https://doi.org/10.1016/j.apmrv.2022.02.002
Meylani, E., Waleleng, G. J., & Kalangi, J. S. (2021). PENGARUH PENGGUNAAN APLIKASI HALODOC TERHADAP PEMENUHAN KEBUTUHAN INFORMASI KESEHATAN di KELURAHAN PANIKI BAWAH KECAMATAN MAPANGET KOTA MANADO.
Ningsi, B. A., & Agustina, L. (2018). Analisis Kepuasan Pelanggan Atas Kualitas Produk dan Pelayanan Dengan Metode SEM-PLS. Jurnal Statistika Dan Aplikasinya (JSA), 2(2).
Octavius, G. S., & Antonio, F. (2021). Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers. International Journal of Telemedicine and Applications, 2021. https://doi.org/10.1155/2021/6698627
Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58. https://doi.org/10.1016/j.ijinfomgt.2021.102310
Prasetio, W., Widyarini, M., & Putrawangsa, D. (2025). Brand Intention, Brand Reliability, and Price on Repurchase Intention of Luxury Products in E-Commerce. Jurnal Wawasan Manajemen, 13(2), 188–198. https://doi.org/10.20527/jwm.v13i2.341
Ratan, R., Earle, K., Rosenthal, S., Hua Chen, V. H., Gambino, A., Goggin, G., Stevens, H., Li, B., & Lee, K. M. (2021). The (digital) medium of mobility is the message: Examining the influence of e-scooter mobile app perceptions on e-scooter use intent. Computers in Human Behavior Reports, 3(December 2020), 100076. https://doi.org/10.1016/j.chbr.2021.100076
Rauschnabel, P. A., He, J., & Ro, Y. K. (2018). Antecedents to the adoption of augmented reality smart glasses: A closer look at privacy risks. Journal of Business Research, 92, 374–384. https://doi.org/10.1016/j.jbusres.2018.08.008
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2020). Handbook of Market Research. In Handbook of Market Research (Issue September). https://doi.org/10.1007/978-3-319-05542-8
Schmitz, A., Díaz-Martín, A. M., & Yagüe Guillén, M. J. (2022). Modifying UTAUT2 for a cross-country comparison of telemedicine adoption. Computers in Human Behavior, 130. https://doi.org/10.1016/j.chb.2022.107183
Stone, R. N., & Grønhaug, K. (2023). Perceived Risk: Further Considerations for the MarketingDiscipline. European Journal of Marketing, 27(3), 39–50. https://doi.org/10.1108/03090569310026637
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2020). User Acceptance of Information Technology: Toward a Unified View. Management Information Systems Quarterly, 27(3), 425–478. https://doi.org/10.1016/j.inoche.2016.03.015
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2022). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. Management Information Systems Quarterly, 36(1), 157–178. https://doi.org/10.1109/MWSYM.2015.7167037
Yan, M., Filieri, R., Raguseo, E., & Gorton, M. (2021). Mobile apps for healthy living: Factors influencing continuance intention for health apps. Technological Forecasting and Social Change, 166. https://doi.org/10.1016/j.techfore.2021.120644
Zhan, X., Abdi, N., Seymour, W., & Such, J. (2024). Healthcare Voice AI Assistants: Factors Influencing Trust and Intention to Use. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1). https://doi.org/10.1145/3637339
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dian Putrawangsa, Audria Ineswari Mulya Marhadi, Hedie Kristiawan, Adi Anggoro Parulian, Thomas Gilbert Alvintra, Avelya Minaka Putri

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain all their rights to the published works, such as (but not limited to) the following rights; Copyright and other proprietary rights relating to the article, such as patent rights, The right to use the substance of the article in own future works, including lectures and books, The right to reproduce the article for own purposes, The right to self-archive the article






